航空学报 > 2026, Vol. 47 Issue (1): 631907-631907   doi: 10.7527/S1000-6893.2025.31907

第二十七届中国科协年会专栏

面向动态需求与可变间隔的eVTOL联合调度方法

袁毓杰1, 李嘉帅1, 赵昕颐2, 王岩韬3()   

  1. 1. 中国民航大学 空中交通管理学院,天津 300300
    2. 武汉大学 电子信息学院,武汉 430072
    3. 中国民航大学 科技创新研究院,天津 300300
  • 收稿日期:2025-02-27 修回日期:2025-03-28 接受日期:2025-05-12 出版日期:2025-06-06 发布日期:2025-06-05
  • 通讯作者: 王岩韬
  • 基金资助:
    天津市科技局自然基金(24JCQNJC00280)

eVTOL scheduling schemes for dynamic demand and variable intervals

Yujie YUAN1, Jiashuai LI1, Xinyi ZHAO2, Yantao WANG3()   

  1. 1. College of Air Traffic Control,Civil Aviation University of China,Tianjin 300300,China
    2. College of Electronic Information,Wuhan University,Wuhan 430072,China
    3. Institute of Science and Technology Innovation,Civil Aviation University of China,Tianjin 300300,China
  • Received:2025-02-27 Revised:2025-03-28 Accepted:2025-05-12 Online:2025-06-06 Published:2025-06-05
  • Contact: Yantao WANG
  • Supported by:
    Tianjin Natural Science Foundation of Science and Technology Bureau(24JCQNJC00280)

摘要:

城市空中交通需要在充分考虑安全约束的同时,以更低运营成本服务更多旅客。对此,提出了电动垂直起降飞行器(eVTOL)低空运营的两阶段联合优化调度方法,首先,阶段1建立了旅客需求预测模型,提出改进的重力模型以挖掘低空网络动态需求波动趋势特征;其次,阶段2面向需求导向建立了以最大旅客周转量和最小总成本为目标函数的安全效益协同优化调度模型。模型以eVTOL性能、航程需求为运行安全和运营成本的基础约束,增设高低流量时变的安全间隔特征、旅客动态流失的决策行为、航程控制的预留电量等可变约束条件;最后,设计了一种联合成本与调度的粒子群优化算法(JOCS-PSO),求解模型最优调度方案。实验结果表明,该方法能有效在线提供eVTOL起飞前的性能优化方案,验证电量预留策略对运营连续性的保障作用和提供电力基础设施支撑能力的计算方法,混合eVTOL配置的利用率提升至77%,起降点内eVTOL额外停留时间不超过12 min,降低了旅客流失率。研究成果在实现成本效益与服务效率平衡的基础上有显著的时间优势,能为城市低空飞行运营管理提供数据与技术支持。

关键词: 动态需求响应, 低空经济, 电动垂直起降航空器(eVTOL), 安全调度计划, 低空飞行安全

Abstract:

The advancement of Urban Air Mobility (UAM) necessitates the development of scheduling methods that not only ensure operational safety but also reduce costs and enhance service capacity. To address this challenge, this paper proposes a two-stage joint optimization scheduling framework for the low-altitude operation of electric Vertical TakeOff and Landing (eVTOL) aircraft. In the first stage, a passenger demand forecasting model is developed. An enhanced gravity model is introduced to capture the spatiotemporal variations and dynamic fluctuation patterns of low-altitude network demand. In the second stage, a demand-responsive scheduling optimization model is formulated, aiming to maximize passenger throughput while minimizing total operational costs. The model incorporates core constraints based on eVTOL performance metrics and range requirements to ensure both flight safety and economic efficiency. Additionally, the model introduces dynamic constraints, including time-varying separation requirements under different traffic volumes, passenger attrition due to delays, and energy reserve margins for range control. To solve this complex optimization problem, a Joint Optimization of Cost and Schedule-Particle Swarm Optimization (JOCS-PSO) algorithm is designed, enabling efficient computation of optimal scheduling schemes. Simulation results demonstrate the effectiveness of the proposed method in generating real-time pre-departure optimization strategies for eVTOL operations. The study validates the role of energy reservation strategies in ensuring operational continuity and presents a quantitative method for assessing the demands on power infrastructure. The utilization rate of a heterogeneous eVTOL fleet is improved to 77%, with additional dwell times at vertiports maintained under 12 minutes, significantly reducing passenger attrition. This research contributes a time-efficient and cost-effective solution to UAM scheduling, offering robust data and technical support for the management of urban low-altitude flight operations.

Key words: dynamic demand, low altitude economy, electric Vertical TakeOff and Landing (eVTOL) aircraft, safety scheduling plan, low-altitude flight safety

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